The present disclosure relates to imaging technologies and the processing of imaging data for the removal of noise.
Medical imaging with ultrasound and MRI imaging relies on detecting low amplitude signals in the radiofrequency spectrum, typically spanning from 2 MHz to 200 MHz. Image quality is greatly influenced by the signal-to-noise ratio. In intravascular ultrasound (IVUS), intracardiac echocardiography (ICE) and other forms of minimally invasive ultrasound, the ultrasound transducer detects ultrasound signals from the surrounding structures and converts the acoustic energy into an electrical signal. This signal is then transmitted along one or more conductive channels (such as coaxial conductors, twisted pair conductors, flex circuits etc.). For many reasons, (including cost, manufacturability, safety, biocompatibility, thermal concerns, and requirements for provision of power) the portion of the minimally invasive imaging probe that can be inserted intracorporeally often does not contain an amplifier to boost the signal strength. The electrical signals detected by minimally invasive ultrasound transducers can be very small (<10 mV and more typically <1 mv), and much of the information about tissue structures that can be imaged with ultrasound tends to lie in the lower portion of the dynamic range of the electrical signals that are detected. The signal amplitude of a received ultrasound signal is limited by any or all of the mechanical efficiency of the transducer, the low amplitude of the acoustic signals detected, the small size of the transducer and attenuation along the conductors that carry the electrical signal from the transducer out of the body. In light of this, the signals in minimally invasive ultrasound imaging systems tend to be very weak.
Noise can be introduced into the system from many sources, including radio transmitters, power electronics, transmission lines, switching transistors and others known in the art. Noise can be introduced via induction or directly via conduction and suboptimal isolation of components that are sensitive to electromagnetic interference. Some of the noise may be generated by components within the imaging system itself, such as scanning actuators, pulse width modulators for motor controllers, switched mode power supplies, clocking circuits and transistors in any of the electronic components of an imaging system. Furthermore, other systems coupled to a patient or in the procedural environment, such as impedance monitors, tracking systems (like those found in Carto® 3, Carto® XP or NavX™ systems), temperature sensors, infusion pumps, ablation systems, ECG and hemodynamic monitors can introduce noise. RFID inventory control systems used in some clinical areas can also introduce noise.
Several approaches are directed at reducing the amount of noise that enters into the ultrasound receive circuitry of ultrasound imaging systems, including selection of components within the system that generate minimal RF noise, electrical isolation, shielding, proper grounding, and physically separating noise-generating components from components that are susceptible to electromagnetic noise. These approaches are often difficult to implement, as the sources of the noise often have preferred characteristics for other reasons (i.e. pulse width modulated motor controllers are energy efficient and have good response times) or are difficult to physically isolate from one another (i.e. it may be desirable to have power electronics in close proximity to the imaging probe or its associated circuitry).
Other approaches for reducing the effect of noise on ultrasound signal quality (and hence ultrasound image quality) include filtering and image processing. Ultrasound signals typically have a known bandwidth and the detected ultrasound signal may be filtered using either analog or digital filtering techniques (often a combination of the two). Analog or digital filtering can be applied to limit the portions of the electrical signal output from the ultrasound receive circuitry to those portions whose frequencies lie within the operational bandwidth (or harmonics thereof) of the ultrasound transducer. Selecting filters with narrow bandwidths and sharp cutoffs can reduce the amount of noise that is allowed into the signals used to generate images or otherwise make use of the ultrasound signals (such as for Doppler measurements spectral analysis of the ultrasound signal, or assessment of flow of scatterers in the sonicated field). Notch or comb filters are helpful in removing narrowband noise within the imaging range of frequencies. Overly aggressive filtering can have the unwanted effect of reducing the amount of signal power that gets accepted for generating images or for other use of the ultrasound signals. It may also negatively impact other performance aspects of an ultrasound imaging system, such as resolution. However, if the passband of the filters is too large, then more noise is accepted into the system.
Image processing can further reduce the noise by filtering the image data generated, such as by averaging or removing outlier values. For example, such filtering can be applied within the image in the spatial domain by applying a Gaussian filter to a pixel and its neighboring pixels in order to blur or smoothen out any random noise in the image. Unfortunately, this tends to reduce the spatial resolution of the image. Similarly, spatial domain filtering can be applied in the structures being imaged that do not move rapidly with respect to the frame repetition frequency of the imaging modality. For example, a pixel in an image frame can be the average or Gaussian-filtered result of the pixels at similar positions in one or more preceding and/or trailing frames.
Similar problems apply to MRI imaging systems, where weak signals are detected in the presence of noise from undesired sources of radiofrequency energy.
What would be very helpful are methods, systems and devices to identify noise and actively remove the noise from one or more imaging signals.
Many forms of noise enter into the ultrasound receive signal chain and can become difficult to remove once they enter the system, especially if they are broadband in nature, wherein a portion of the noise lies within the passband of the ultrasound system. For example, in an imaging system that has a transducer with a center frequency of 10 MHz, and a passband of 7.5 to 12.5 MHz, the system may be designed to heavily filter out any portions of the noise that are less than 7.5 MHz and any portions of the noise that are more than 12.5 MHz. Unfortunately, the amplitude of the noise within the 7.5-12.5 MHz bandpass may frequently be appreciable relative to the amplitude of the ultrasound signal that is being detected.
Many sources of noise occur as a result of rapid transients, such as when a field effect transistor or switch turns on or off. An electrical signal with rapid transients in it has a very broad frequency domain representation that can easily span all or a portion of the passband of the ultrasound receive signal chain. This is particularly true of power supplies or pulse width modulation circuits where the noise can have a strong enough amplitude to compete with the signal being detected.